August 19, 2017
100 deaths daily.
Impact on malaria incidence (burden)
Impact on labour force (absenteeism and productivity)
3. Impact on school age children (absenteeism and performance)
| Characteristic | Manhiça | Magude |
|---|---|---|
| Age mean | 9.37 | 9.16 |
| age SD | 2.71 | 2.78 |
| conditions score SD | 3986.16 | 4150.42 |
| Education mean | 2.38 | 2.53 |
| education SD | 1.16 | 1.46 |
| Females | 2352.00 | 750.00 |
| Males | 2445.00 | 708.00 |
| N | 6191.00 | 2612.00 |
| Ses asset score mean | 6976.67 | 6752.86 |
| ses asset score SD | 971.98 | 805.78 |
| Siblings mean | 4.49 | 4.40 |
| siblings SD | 2.53 | 2.84 |
In diff-diff models: assumption: parallel trends (in the outcome variable) in treatment and control groups before the introduction of the intervention In order to check this crucial assumption…
The coefficients for the interaction between trimester and intervention area identify the differential trends in the outcome variable over time between the treated and control regions. Thus, as the policy is implemented in 2016, these coefficients identify any differential pre-trends in the outcome variable between treated and control regions (the crucial assumption for diff-diff models).
| Term | Key | 1 | 2 | 3 |
|---|---|---|---|---|
| After | Estimate | 0.004 | 0.004 | 0.004 |
| P | 0.021 | 0.004 | 0.004 | |
| S.E. | 0.002 | 0.001 | 0.001 | |
| After:Intervention | Estimate | 0.016 | 0.017 | 0.017 |
| P | < 0.001 | < 0.001 | < 0.001 | |
| S.E. | 0.003 | 0.003 | 0.003 | |
| (Intercept) | Estimate | 0.867 | 0.962 | 0.962 |
| P | < 0.001 | < 0.001 | < 0.001 | |
| S.E. | 0.002 | 0.002 | 0.002 | |
| Intervention | Estimate | 0.047 | 0.039 | 0.039 |
| P | < 0.001 | < 0.001 | < 0.001 | |
| S.E. | 0.005 | 0.005 | 0.005 |
All regressions controlling for school. Regressions II and III also controlling for subject.
**The impact of the policy is to increase the probability of passing the exam by 2 percentage points. Given that the proportion of those passing examinations was 87.5% in the intervention area in 2015, the increase due to the intervention is (0.02/0.875*100) 2.28%.**
| Term | Key | value |
|---|---|---|
| After | Estimate | 0.008 |
| S.E. | 0.005 | |
| P | 0.151 | |
| factor(trimester)2 | Estimate | < 0.001 |
| S.E. | 0.005 | |
| P | 0.007 | |
| factor(trimester)3 | Estimate | < 0.001 |
| S.E. | 0.006 | |
| P | < 0.001 | |
| After:Intervention | Estimate | 0.047 |
| S.E. | 0.01 | |
| P | < 0.001 | |
| (Intercept) | Estimate | 0.784 |
| S.E. | 0.007 | |
| P | < 0.001 | |
| Intervention | Estimate | 0.029 |
| S.E. | 0.018 | |
| P | 0.105 |
The impact of the policy is to increase the probability of passing the exam by 5 percentage points for the case of maths. Given that the proportion of those passing examinations was 76.69% in the intervention area in 2015, the increase due to the intervention is (0.05/0.7669*100) 6.52%.
OLS regression; regression controlling for school (coeff not shown);
| Term | Key | 1 | 2 | 3 |
|---|---|---|---|---|
| After | Estimate | 0.198 | 0.201 | 0.201 |
| P | < 0.001 | < 0.001 | < 0.001 | |
| S.E. | 0.014 | 0.014 | 0.014 | |
| After:Intervention | Estimate | 0.166 | 0.171 | 0.171 |
| P | < 0.001 | < 0.001 | < 0.001 | |
| S.E. | 0.027 | 0.027 | 0.027 | |
| (Intercept) | Estimate | 11.832 | 12.185 | 12.174 |
| P | < 0.001 | < 0.001 | < 0.001 | |
| S.E. | 0.015 | 0.021 | 0.022 | |
| Intervention | Estimate | 0.029 | < 0.001 | < 0.001 |
| P | 0.55 | 0.641 | 0.641 | |
| S.E. | 0.048 | 0.047 | 0.047 |
The impact of the policy is to increase the grade for all subjects by 0.23 percentage points. Given that the mean grade was 12.11 in the intervention area in 2015, the increase due to the intervention is (0.22/12.11*100) 1.9%.
| Term | Key | value |
|---|---|---|
| After | Estimate | 0.196 |
| S.E. | 0.047 | |
| P | < 0.001 | |
| factor(trimester)2 | Estimate | < 0.001 |
| S.E. | 0.048 | |
| P | < 0.001 | |
| factor(trimester)3 | Estimate | < 0.001 |
| S.E. | 0.049 | |
| P | < 0.001 | |
| After:Intervention | Estimate | 0.408 |
| S.E. | 0.09 | |
| P | < 0.001 | |
| (Intercept) | Estimate | 12.093 |
| S.E. | 0.059 | |
| P | < 0.001 | |
| Intervention | Estimate | < 0.001 |
| S.E. | 0.159 | |
| P | 0.01 |
| Term | Key | value |
|---|---|---|
| (Intercept) | Estimate | 0.942 |
| Estimate | 0.056 | |
| -1 Period | Estimate | < 0.001 |
| 1 Period | Estimate | 0.005 |
| -2 Period | Estimate | < 0.001 |
| 2 Period | Estimate | < 0.001 |
| -3 Period | Estimate | 0.001 |
| 0 Time::Intervention | Estimate | 0.023 |
| -1 Time::Intervention | Estimate | 0.011 |
| 1 Time::Intervention | Estimate | 0.022 |
| -2 Time::Intervention | Estimate | 0.006 |
| 2 Time::Intervention | Estimate | 0.023 |
| Term | Key | value |
|---|---|---|
| (Intercept) | Estimate | 0.711 |
| S.E. | 0.021 | |
| P | < 0.001 | |
| Estimate | 0.087 | |
| S.E. | 0.02 | |
| P | < 0.001 | |
| -1 Period | Estimate | < 0.001 |
| S.E. | 0.009 | |
| P | 0.004 | |
| 1 Period | Estimate | 0.001 |
| S.E. | 0.009 | |
| P | 0.888 | |
| -2 Period | Estimate | < 0.001 |
| S.E. | 0.009 | |
| P | 0.022 | |
| 2 Period | Estimate | < 0.001 |
| S.E. | 0.009 | |
| P | 0.206 | |
| -3 Period | Estimate | 0.014 |
| S.E. | 0.009 | |
| P | 0.129 | |
| 0 Time::Intervention | Estimate | 0.071 |
| S.E. | 0.017 | |
| P | < 0.001 | |
| -1 Time::Intervention | Estimate | 0.021 |
| S.E. | 0.019 | |
| P | 0.249 | |
| 1 Time::Intervention | Estimate | 0.062 |
| S.E. | 0.018 | |
| P | < 0.001 | |
| -2 Time::Intervention | Estimate | 0.016 |
| S.E. | 0.018 | |
| P | 0.373 | |
| 2 Time::Intervention | Estimate | 0.046 |
| S.E. | 0.018 | |
| P | 0.009 |
Showing the difference between 2015 and 2016 average grades
Call:
lm(formula = value ~ district + factor(year) + district * factor(year),
data = aprop)
Residuals:
Min 1Q Median 3Q Max
-12.3761 -1.5120 -0.1547 1.6239 7.8453
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 12.15468 0.01810 671.686 < 2e-16 ***
districtManhiça 0.08903 0.02439 3.650 0.000262 ***
factor(year)2016 0.35736 0.02394 14.926 < 2e-16 ***
districtManhiça:factor(year)2016 -0.22500 0.03240 -6.945 3.8e-12 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 2.838 on 126050 degrees of freedom
Multiple R-squared: 0.002106, Adjusted R-squared: 0.002082
F-statistic: 88.67 on 3 and 126050 DF, p-value: < 2.2e-16
Call:
lm(formula = value ~ district + factor(year) + district * factor(year),
data = lluny)
Residuals:
Min 1Q Median 3Q Max
-12.3052 -1.5268 -0.1547 1.6948 7.8453
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 12.15468 0.01727 703.913 < 2e-16 ***
districtManhiça 0.15053 0.02148 7.007 2.45e-12 ***
factor(year)2016 0.35736 0.02285 15.642 < 2e-16 ***
districtManhiça:factor(year)2016 -0.13579 0.02921 -4.649 3.33e-06 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 2.708 on 145989 degrees of freedom
Multiple R-squared: 0.002785, Adjusted R-squared: 0.002764
F-statistic: 135.9 on 3 and 145989 DF, p-value: < 2.2e-16
Call:
lm(formula = value ~ district + factor(year) + district * factor(year),
data = lluny)
Residuals:
Min 1Q Median 3Q Max
-12.3052 -1.5268 -0.3052 1.6948 7.9429
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 12.30521 0.01260 976.907 < 2e-16 ***
districtMagude -0.24810 0.04067 -6.101 1.06e-09 ***
factor(year)2016 0.22156 0.01793 12.357 < 2e-16 ***
districtMagude:factor(year)2016 0.14388 0.05175 2.780 0.00543 **
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 2.669 on 101644 degrees of freedom
Multiple R-squared: 0.002302, Adjusted R-squared: 0.002272
F-statistic: 78.17 on 3 and 101644 DF, p-value: < 2.2e-16
2985 of 4958 (60.21%)
(One observation = 1 trimester-class)
(One observation = 1 trimester-class)
Error in -n: invalid argument to unary operator
Error in -n: invalid argument to unary operator
Error in -n: invalid argument to unary operator
of 4510 (%)
(One observation = 1 student-day)
(One observation = 1 student-day)
Error in summarise_impl(.data, dots): invalid 'type' (closure) of argument
596685 student-days observed (absenteeism)
214675 student-class-trimesters observed (performance)